Silver microspheres aggregation-induced Raman enhanced scattering used for rapid detection of carbendazim in Chinese tea

An electrochemiluminescence strategy with proximity ligation triggered multiple catalytic hairpin assembly induced CRISPR/Cas 12a system for analysis of paraquat

Paraquat (PQ) as a widely used non-selective herbicides has gained attention in agricultural residue detection and food safety. Herein, a novel quantitative analysis approach for PQ was proposed based on a novel kind of aggregation-induced emission electrochemiluminescence (AIECL) emitters, tetraphenylethylene-luminol (TPE-L) with a small molecule-induced multiple catalytic hairpin assembly (CHA) amplification strategy, the competitive immune reaction and CRISPR/Cas12a system. The target molecule PQ is introduced into a signal cycle, and auxiliary sensitization cycles are constructed by virtue of the cleavage characteristics of the CRISPR/Cas12a system, which realized the multiple utilization of the target by using both cis- and trans-cleavage activities. In addition, the new multiple CHA amplification strategy was attributed to cross-catalytic hairpin assembly caused by the products of the CHA cycle as the initiator chain of the next CHA cycle, realizing the efficient utilization of cyclic products and producing high-efficiency signal amplification. Thus, the ECL biosensor for ultrasensitive analysis of PQ was successfully constructed with a limit of detection of 0.7 pg/mL. Importantly, it could be easily-extended to other small molecules simply by replacing paired antibodies, providing prospects in agricultural residue detection, food safety and related medical applications.

SERS Detection of Hydrophobic Molecules: Thio-β-Cyclodextrin-Driven Rapid Self-Assembly of Uniform Silver Nanoparticle Monolayers and Analyte Trapping

High-sensitivity and repeatable detection of hydrophobic molecules through the surface-enhanced Raman scattering (SERS) technique is a tough challenge because of their weak adsorption and non-uniform distribution on SERS substrates. In this research, we present a simple self-assembly protocol for monolayer SERS mediated by 6-deoxy-6-thio-β-cyclodextrin (β-CD-SH). This protocol allows for the rapid assembly of a compact silver nanoparticle (Ag NP) monolayer at the oil/water interface within 40 s, while entrapping analyte molecules within hotspots. The proposed method shows general applicability for detecting hydrophobic molecules, exemplified as Nile blue, Nile red, fluconazole, carbendazim, benz[a]anthracene, and bisphenol A. The detection limits range from 10-6to 10-9 M, and the relative standard deviations (RSDs) of signal intensity are less than 10%. Moreover, this method was used to investigate the release behaviors of a hydrophobic pollutant (Nile blue) adsorbed on the nanoplastic surface in the water environment. The results suggest that elevated temperatures, increased salinities, and the coexistence of fulvic acid promote the release of Nile blue. This simple and fast protocol overcomes the difficulties related to hotspot accessibility and detection repeatability for hydrophobic analytes, holding out extensive application prospects in environmental monitoring and chemical analysis.

Microfluidics-aided fabrication of 3D micro-nano hierarchical SERS substrate for rapid detection of dual hepatocellular carcinoma biomarkers

The simultaneous analysis of trace amounts of dual biomarkers is crucial in the early diagnosis, treatment, and prognosis of hepatocellular carcinoma (HCC). In this study, we prepared SERS-active hydrogel microparticles (SAHMs) with 3D hierarchical gold nanoparticles (AuNPs) micro-nanostructures by microdroplet technology and in situ synthesis, which demonstrated high reproducibility and sensitivity. Compared with traditional 2D SERS substrates, this newly prepared 3D SERS substrate provided a high density of nano-wrinkled structures and numerous AuNPs. Furthermore, a newly designed SERS-active substrate was proposed for the simultaneous microfluidic detection of AFP and AFU. The Raman signals of sandwich immunocomplexes on the surface of the SAHMs were measured for the trace analysis of these biomarkers. The proposed microfluidic platform achieved AFP and AFU detection in the range of 0.1-100 ng mL-1 and 0.01-100 ng mL-1, respectively, which represents a good response. Indeed, this platform is easy to fabricate, of low cost and has short detection time and comparable detection limits to other methods. As far as we know, this is the first study to achieve the simultaneous detection of AFP and AFU on a microfluidic platform. Therefore, we proposed a new simultaneous detection platform for dual HCC biomarkers that shows strong potential for the early diagnosis of HCC.

Core-shell structure DA-CDs/AuNPs for the recognition of fenamidone by surface-enhanced Raman scattering

In this work, a facile synthesis method for dopamine carbon dots-based Au nanoparticles (DA-CDs/AuNPs) by seed gold method was reported as the surface enhanced Raman scattering (SERS) booster. DA-CDs with rich in surface functional groups was synthesized using dopamine, citric acid and ethylenediamine as precursors by a facile hydrothermal method, and can be used as the capping agents and reducing agents for the synthesis of DA-CDs/AuNPs. Due to the electromagnetic "hot spots" effect, DA-CDs/AuNPs with core-shell structure exhibited strong SERS activity. Based on the specific interaction of DA-CDs/AuNPs and fenamidone, a detection method of fenamidone was established with a low detection limit of 0.05 μg/mL. Finally, the SERS sensor was successfully applied to the detection of fenamidone in fruit with recoveries between 90.6 % and 98.7 %. The method here proposed can be reliably applied for fenamidone detection on fruits.

Ultrasensitive quantitation of Paraquat based on a small molecule-induced dual-cycle amplification strategy

Paraquat (PQ) is a typical biotoxic small molecule. Knowledge of how to directly introduce it into cyclic amplification rather than transform it into a secondary target is lacking in current analytical methods. Considering the urgent need for trace pesticide residue detection and the inherent defects of small molecule analysis, a CRISPR/Cas12a-driven small molecule-induced dual-cycle strategy was developed based on the immune competition method. The key to signal amplification is the mutual activation and acceleration between Cycle 1 triggered by the small molecule and Cycle 2 driven by CRISPR/Cas12a. Impressively, small molecules have been successfully incorporated into the dual-cycle strategy, which achieves a low detection limit (3.1 pg/mL) and a wide linear range (from 10 pg/mL to 50 μg/mL). Moreover, the designed biosensor was successfully employed to evaluate the PQ residual level in real samples and showed effective implementation for the bioanalysis of small molecule targets and pesticide residue-related food safety.

Introduction of multilayered quantum dot nanobeads into competitive lateral flow assays for ultrasensitive and quantitative monitoring of pesticides in complex samples

A competitive fluorescent lateral flow assay (CFLFA) is proposed for direct, ultrasensitive, quantitative detection of common pesticides imidacloprid (IMI) and carbendazim (CBZ) in complex food samples by using silica-core multilayered quantum dot nanobeads (SiO2-MQB) as liquid fluorescent tags. The SiO2-MQB nanostructure comprises a 200-nm SiO2 core and a shell of hundreds of carboxylated QDs (excitation/emission maxima ~365/631 nm), and can generate better stability, superior dispersibility, and higher luminescence than traditional fluorescent beads, greatly improving the sensitivity of current LFA methods for pesticides. Moreover, using liquid SiO2-MQB directly instead of via the conjugate pad both simplifies the structure of LFA system and improves the efficiency of immunobinding reactions between nanotags and the targets. Applying these methods, the established CFLFA realized the stable and accurate detection of IMI and CBZ in 12 min, with detection limits down to 1.94 and 14.79 pg/mL, respectively. The SiO2-MQB-CFLFA is practicable for application to real food samples (corn, apple, cucumber, and cabbage), and undoubtedly a promising and low-cost tool for on-site monitoring of trace pesticide residues.

Highly sensitive fluorescent quantification of carbendazim by two-dimensional Tb-MOF nanosheets for food safety

Carbendazim (CBZ), a well-known benzimidazole pesticide, is utilized in agriculture to prevent and cure plant diseases caused by fungi. Residual CBZ in food poses serious threat to human health. Herein, a fluorescent two-dimensional terbium-based metal-organic framework (2D Tb-MOF) nanosheet sensor was developed for the rapid and ultrasensitive detection of CBZ. The 2D Tb-MOF nanosheets, prepared with Tb³⁺ ions and 5-borono-1,3-benzenedicarboxylic acid (BBDC) as the precursors, exhibited excellent optical properties. Upon the addition of CBZ, the fluorescence of Tb-MOF nanosheets was quenched because of the inner filter effect (IFE) and dynamic quenching. The fluorescence sensor offered two linear ranges of 0.06-4 and 4-40 µg/mL with a low detection limit of 17.95 ng/mL. Furthermore, the proposed sensing platform was successfully applied to assay CBZ in apples and tea, and satisfactory results were obtained. This study provides an effective alternative strategy for the qualitative and quantitative determination of CBZ to ensure food safety.

Au-Ag OHCs-based SERS sensor coupled with deep learning CNN algorithm to quantify thiram and pymetrozine in tea

Pesticide residue detection in food has become increasingly important. Herein, surface-enhanced Raman scattering (SERS) coupled with an intelligent algorithm was developed for the rapid and sensitive detection of pesticide residues in tea. By employing octahedral Cu₂O templates, Au-Ag octahedral hollow cages (Au-Ag OHCs) were developed, which improved the surface plasma effect via rough edges and hollow inner structure, amplifying the Raman signals of pesticide molecules. Afterward, convolutional neural network (CNN), partial least squares (PLS), and extreme learning machine (ELM) algorithms were applied for the quantitative prediction of thiram and pymetrozine. CNN algorithms performed optimally for thiram and pymetrozine, with correlation values of 0.995 and 0.977 and detection limits (LOD) of 0.286 and 29 ppb, respectively. Accordingly, no significant difference (P greater than 0.05) was observed between the developed approach and HPLC in detecting tea samples. Hence, the proposed Au-Ag OHCs-based SERS technique could be utilized for quantifying thiram and pymetrozine in tea.

Core-shell Au@ZIF-67-based pollutant monitoring of thiram and carbendazim pesticides

A sensitive and stable substrate plays a vital role in the Raman spectroscopic techniques as an analytical method for detecting pesticides effectively from the environment. Enhancing signals from nanoparticles are weak and inconsistent in repeatability since analytes tend to degrade quickly under laser exposure. Herein, a novel substrate of Au@ZIF-67 is prepared on octahedral AuNPs by trapping pesticide molecules with small three-dimensional volumes by the flexibility of ZIF-67 for rapid detection with high sensitivity and stability. The two types of thiram and carbendazim pesticides, which are environmental pollutants that affect biodiversity, were successfully absorbed in Au@ZIF-67 nanostructures by adsorption-desorption equilibrium for analytical purposes in Raman spectroscopy. Spectra calculations of the thiram and carbendazim molecules on 8 atoms of Au using DFT were compared with the experimental data. The SERS enhancement factors for thiram and carbendazim were estimated to be 1.91 × 10⁸ and 3.12 × 10⁸, respectively, with the LOD values of trace amounts of ∼10^-10 mol L^-1. The novel substrate of Au@ZIF-67 is a propitious platform for detecting thiram and carbendazim in trace amounts, providing a helpful strategy for detecting residues with high performance in the environment at the laboratory and practical scales.

Rapid Detection of Carbendazim Residue in Apple Using Surface-Enhanced Raman Scattering and Coupled Chemometric Algorithm

In order to achieve rapid and precise quantification detection of carbendazim residues, surface-enhanced Raman spectroscopy (SERS) combined with variable selected regression methods were developed. A higher sensitivity and greater density of "hot spots" in three-dimensional (3D) SERS substrates based on silver nanoparticles compound polyacrylonitrile (Ag-NPs @PAN) nanohump arrays were fabricated to capture and amplify the SERS signal of carbendazim. Four Raman spectral variable selection regression models were established and comparatively assessed. The results showed that the bootstrapping soft shrinkage-partial least squares (BOSS-PLS) method achieved the best predictive capacity after variable selection, and the final BOSS-PLS model has the correlation coefficient (R_P) of 0.992. Then, this method used to detect the carbendazim residue in apple samples; the recoveries were 86~116%, and relative standard deviation (RSD) is less than 10%. The 3D SERS substrates combined with the BOSS-PLS algorithm can deliver a simple and accurate method for trace detection of carbendazim residues in apples.

Tunable multiplexed fluorescence biosensing platform for simultaneous and selective detection of paraquat and carbendazim pesticides

The monitoring of multiple pesticides commonly used in food is a prerequisite for public health safety. Herein, a multiplexed biosensor based on fluorescence resonance energy transfer (FRET) from multicolor upconversion nanoparticles (UCNPs)to single black phosphorus nanosheets (BPNSs) was successfully developed for simultaneous and selective detection of paraquat and carbendazim pesticides. Due to the strong π-π stacking interactions, aptamers functionalized UCNPs may adsorb on the BPNSs surface, allowing strong upconversion fluorescence quenching. In the presence of paraquat and carbendazim, the aptamers preferentially integrated with their corresponding targets and altered the aptamer's conformation, restoring the fluorescence. An excellent linear correlation was observed from 1.0 to 1.0 × 10⁵ ng/mL, with a limit of detection of 0.18 ng/mL for paraquat and 0.45 ng/mL for carbendazim. The developed aptasensor was further validated by commercial enzyme-linked immunoassays without significant differences in practical detection. Additionally, this work offers new insights into monitoring multiple targets simultaneously.

Applications of surface-enhanced Raman spectroscopy in environmental detection

As the human population grows, the anthropogenic impacts from various agricultural and industrial processes produce unwanted contaminants in the environment. The accurate, sensitive and rapid detection of such contaminants is vital for human health and safety. Surface-enhanced Raman spectroscopy (SERS) is a valuable analytical tool with wide applications in environmental contaminant monitoring. The aim of this review is to summarize recent advancements within SERS research as it applies to environmental detection, with a focus on research published or accessible from January 2021 through December 2021 including early-access publications. Our goal is to provide a wide breadth of information that can be used to provide background knowledge of the field, as well as inform and encourage further development of SERS techniques in protecting environmental quality and safety. Specifically, we highlight the characteristics of effective SERS nanosubstrates, and explore methods for the SERS detection of inorganic, organic, and biological contaminants including heavy metals, pharmaceuticals, plastic particles, synthetic dyes, pesticides, viruses, bacteria and mycotoxins. We also discuss the current limitations of SERS technologies in environmental detection and propose several avenues for future investigation. We encourage researchers to fill in the identified gaps so that SERS can be implemented in a real-world environment more effectively and efficiently, ultimately providing reliable and timely data to help and make science-based strategies and policies to protect environmental safety and public health.

Rapid field trace detection of pesticide residue in food based on surface-enhanced Raman spectroscopy

Surface-enhanced Raman spectroscopy is an alternative detection tool for monitoring food security. However, there is still a lack of a conclusion of SERS detection with respect to pesticides and real sample analysis, and the summary of intelligent algorithms in SERS is also a blank. In this review, a comprehensive report of pesticides detection using SERS technology is given. The SERS detection characteristics of different types of pesticides and the influence of substrate on inspection are discussed and compared by the typical ways of classification. The key points, including the progress in real sample analysis and Raman data processing methods with intelligent algorithm, are highlighted. Lastly, major challenges and future research trends of SERS analysis of pesticide residue are also addressed. SERS has been proven to be a powerful technique for rapid test of residue pesticides in complex food matrices, but there still is a tremendous development space for future research.

A multicolor enzyme-linked immunoassay method for visual readout of carbendazim

Enzyme-linked immunosorbent assay (ELISA) with high specificity and sensitivity is one of the most popular techniques for detecting carbendazim (CBD), a commonly used benzimidazole fungicide in agriculture. However, the traditional ELISA based on the horseradish peroxidase (HRP)-3,3',5,5'-tetramethylbenzidine (TMB) system for CBD only displays the yellow color of TMB²⁺ from deep to light, making it difficult for the naked eye to judge whether CBD in fruits and vegetables exceeds the maximum residue limit. In this article, we intend to improve the traditional ELISA method to establish a multicolor signal output ELISA to achieve visual semiquantitative detection of CBD. This method is based on the optical properties of gold nanorods (AuNRs). After introducing AuNRs into TMB²⁺ solution, which was produced by the HRP-TMB system of traditional ELISA, AuNRs were quickly etched by TMB²⁺. Consequently, the longitudinal localized surface plasmon resonance peak of AuNRs shows a clear blue shift and a vivid color change. Different concentrations of CBD generate different amounts of TMB²⁺, which in turn leads to different etching degrees of AuNRs, and ultimately results in a rainbow-like color change. As a result, CBD from 0.08 to 100 ng mL^-1 can be easily distinguished by the naked eye, which does not require any large instruments. Moreover, the colors displayed by 0.49 ng mL^-1 (purple) and 0 ng mL^-1 (pink) are significantly different from each other. It should be noted that 0.49 ng mL^-1 is far below the most stringent maximum residue limit of CBD in the world. Additionally, the quantitative determination of CBD spiked in canned citrus, citrus fruits, chives, and cabbage samples showed satisfactory recoveries. The good performance of the AuNR-based ELISA makes it have a wide range of application prospects in food safety and international trade.

Recent advances of nanomaterial-based optical sensor for the detection of benzimidazole fungicides in food: a review

The abuse of pesticides in agricultural land during pre- and post-harvest causes an increase of residue in agricultural products and pollution in the environment, which ultimately affects human health. Hence, it is crucially important to develop an effective detection method to quantify the trace amount of residue in food and water. However, with the rapid development of nanotechnology and considering the exclusive properties of nanomaterials, optical, and their integrated system have gained exclusive interest for accurately sensing of pesticides in food and agricultural samples to ensure food safety thanks to their unique benefit of high sensitivity, low detection limit, good selectivity and so on and making them a trending hotspot. This review focuses on recent progress in the past five years on nanomaterial-based optical, such as colorimetric, fluorescence, surface-enhanced Raman scattering (SERS), and their integrated system for the monitoring of benzimidazole fungicide (including, carbendazim, thiabendazole, and thiophanate-methyl) residue in food and water samples. This review firstly provides a brief introduction to mentioned techniques, detection mechanism, applied nanomaterials, label-free detection, target-specific detection, etc. then their specific application. Finally, challenges and perspectives in the respective field are discussed.